The new frontiers of environmentalism will be played out in combined human and natural spaces. Sustainability is not possible in a world where communities struggle for basic survival—people will prioritize fuelwood over pandas, homes over fish habitat, and agriculture over forests. Natural resource scientists and managers are not new to the idea that human communities can be solutions as well as problems. The last few decades have marked new inroads in collaborative (co-) management with mixed results, in large part because the standards of what makes good community engagement in the natural resources arena are still being decided. This research hopes to serve as an early bridge to link natural resource scientists with community engagement scholarship, a field dedicated to working with communities to develop long term, sustainable solutions to human problems. For community-engagement scholars, who often work on small scales with specific programs and projects, this research can serve as an advancement of thinking about engagement in a larger management scale.In Chapter 1, I use a content analysis technique to help to bridge the language divide between these two fields. This chapter attempts to overcome the first hurdle in interdisciplinary research: helping researchers from different disciplines understand each other. The chapter successfully uses an iterative methodology to uncover some of the most common terms being used in natural resources fields to describe community engagement initiatives, starting only with the name of a field of interest and a term already familiar to community engagement scholars.In Chapters 2 and 3, I move from theory into practice. In Chapter 2, I combine the risk ladder from natural resources human dimension research with the Q-sort, a methodology designed in the field of psychology for comparing various issues against each other. The result is the Riley Risk Ladder, which allows for the quantitative measurement of multiple costs and benefits from both the probability and magnitude dimensions of risk in addition to qualitative data collected during the interview. In Chapter 3, I use the Riley Risk Ladder in a group setting which has the possibility of collecting similar data with a lower investment of time and resources. This chapter explores how conducting the interview in a group setting changes what sorts of results can be seen and discusses what mechanisms can be put in place to reduce confounding group dynamics such as groupthink, social desirability, and anchoring.Finally, Chapter 4 takes the interview data back to the stakeholders, reaching out in partnership to the stakeholder groups that participated in the original interview work. It explores the process of working with partners to develop a set of research questions, and takes a look at some of the obstacles of bridging the divide between partners from typically natural science backgrounds and working with social science data.
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